Browsing by Author "Heckbert, Susan R."
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Item Clinical characteristics and 12-month outcomes of patients with valvular and non-valvular atrial fibrillation in Kenya(PLOS, 2017-09-21) Temu, Tecla M.; Lane, Kathleen A.; Shen, Changyu; Ng'ang'a, Loise; Akwanalo, Constantine O.; Chen, Peng-Sheng; Emonyi, Wilfred; Heckbert, Susan R.; Koech, Myra M.; Manji, Imran; Vatta, Matteo; Velazquez, Eric J.; Wessel, Jennifer; Kimaiyo, Sylvester; Inui, Thomas S.; Bloomfield, Gerald S.; Biostatistics, School of Public HealthBackground Atrial fibrillation (AF) is a major contributor to the global cardiovascular disease burden. The clinical profile and outcomes of AF patients with valvular heart diseases in sub-Saharan Africa (SSA) have not been adequately described. We assessed clinical features and 12-month outcomes of patients with valvular AF (vAF) in comparison to AF patients without valvular heart disease (nvAF) in western Kenya. Methods We performed a cohort study with retrospective data gathering to characterize risk factors and prospective data collection to characterize their hospitalization, stroke and mortality rates. Results The AF patients included 77 with vAF and 69 with nvAF. The mean (SD) age of vAF and nvAF patients were 37.9(14.5) and 69.4(12.3) years, respectively. There were significant differences (p<0.001) between vAF and nvAF patients with respect to female sex (78% vs. 55%), rates of hypertension (29% vs. 73%) and heart failure (10% vs. 49%). vAF patients were more likely to be taking anticoagulation therapy compared to those with nvAF (97% vs. 76%; p<0.01). After 12-months of follow-up, the overall mortality, hospitalization and stroke rates for vAF patients were high, at 10%, 34% and 5% respectively, and were similar to the rates in the nvAF patients (15%, 36%, and 5%, respectively). Conclusion Despite younger age and few comorbid conditions, patients with vAF in this developing country setting are at high risk for nonfatal and fatal outcomes, and are in need of interventions to improve short and long-term outcomes.Item Early Cumulative Fluid Balance and Outcomes in Pediatric Allogeneic Hematopoietic Cell Transplant Recipients With Acute Respiratory Failure: A Multicenter Study(Frontiers Media, 2021-07-20) Sallee, Colin J.; Smith, Lincoln S.; Rowan, Courtney M.; Heckbert, Susan R.; Angelo, Joseph R.; Daniel, Megan C.; Gertz, Shira J.; Hsing, Deyin D.; Mahadeo, Kris M.; McArthur, Jennifer A.; Fitzgerald, Julie C.; Pediatrics, School of MedicineObjectives: To evaluate the associations between early cumulative fluid balance (CFB) and outcomes among critically ill pediatric allogeneic hematopoietic cell transplant (HCT) recipients with acute respiratory failure, and determine if these associations vary by treatment with renal replacement therapy (RRT). Methods: We performed a secondary analysis of a multicenter retrospective cohort of patients (1mo - 21yrs) post-allogeneic HCT with acute respiratory failure treated with invasive mechanical ventilation (IMV) from 2009 to 2014. Fluid intake and output were measured daily for the first week of IMV (day 0 = day of intubation). The exposure, day 3 CFB (CFB from day 0 through day 3 of IMV), was calculated using the equation [Fluid in - Fluid out] (liters)/[PICU admission weight] (kg)*100. We measured the association between day 3 CFB and PICU mortality with logistic regression, and the rate of extubation at 28 and 60 days with competing risk regression (PICU mortality = competing risk). Results: 198 patients were included in the study. Mean % CFB for the cohort was positive on day 0 of IMV, and increased further on days 1-7 of IMV. For each 1% increase in day 3 CFB, the odds of PICU mortality were 3% higher (adjusted odds ratio (aOR) 1.03, 95% CI 1.00-1.07), and the rate of extubation was 3% lower at 28 days (adjusted subdistribution hazard ratio (aSHR) 0.97, 95% CI 0.95-0.98) and 3% lower at 60 days (aSHR 0.97, 95% CI 0.95-0.98). When day 3 CFB was dichotomized, 161 (81%) had positive and 37 (19%) had negative day 3 CFB. Positive day 3 CFB was associated with higher PICU mortality (aOR 3.42, 95% CI 1.48-7.87) and a lower rate of extubation at 28 days (aSHR 0.30, 95% CI 0.18-0.48) and 60 days (aSHR 0.30, 95% 0.19-0.48). On stratified analysis, the association between positive day 3 CFB and PICU mortality was significantly stronger in those not treated with RRT (no RRT: aOR 9.11, 95% CI 2.29-36.22; RRT: aOR 1.40, 95% CI 0.42-4.74). Conclusions: Among critically ill pediatric allogeneic HCT recipients with acute respiratory failure, positive and increasing early CFB were independently associated with adverse outcomes.Item Genetic and clinical correlates of two neuroanatomical AI dimensions in the Alzheimer's disease continuum(Springer Nature, 2024-10-05) Wen, Junhao; Yang, Zhijian; Nasrallah, Ilya M.; Cui, Yuhan; Erus, Guray; Srinivasan, Dhivya; Abdulkadir, Ahmed; Mamourian, Elizabeth; Hwang, Gyujoon; Singh, Ashish; Bergman, Mark; Bao, Jingxuan; Varol, Erdem; Zhou, Zhen; Boquet-Pujadas, Aleix; Chen, Jiong; Toga, Arthur W.; Saykin, Andrew J.; Hohman, Timothy J.; Thompson, Paul M.; Villeneuve, Sylvia; Gollub, Randy; Sotiras, Aristeidis; Wittfeld, Katharina; Grabe, Hans J.; Tosun, Duygu; Bilgel, Murat; An, Yang; Marcus, Daniel S.; LaMontagne, Pamela; Benzinger, Tammie L.; Heckbert, Susan R.; Austin, Thomas R.; Launer, Lenore J.; Espeland, Mark; Masters, Colin L.; Maruff, Paul; Fripp, Jurgen; Johnson, Sterling C.; Morris, John C.; Albert, Marilyn S.; Bryan, R. Nick; Resnick, Susan M.; Ferrucci, Luigi; Fan, Yong; Habes, Mohamad; Wolk, David; Shen, Li; Shou, Haochang; Davatzikos, Christos; Radiology and Imaging Sciences, School of MedicineAlzheimer's disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised representation learning technique known as Surreal-GAN, through which we identified two latent dimensional representations of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE ε4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE ε4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction-driven by genes different from APOE-which may collectively contribute to the early pathogenesis of AD. All results are publicly available at https://labs-laboratory.com/medicine/ .Item Genetic mutations in African patients with atrial fibrillation: Rationale and design of the Study of Genetics of Atrial Fibrillation in an African Population (SIGNAL)(Elsevier, 2015-09) Bloomfield, Gerald S.; Temu, Tecla; Akwanalo, Constantine O.; Chen, Peng-Sheng; Emonyi, Wilfred; Heckbert, Susan R.; Koech, Myra M.; Manji, Imran; Shen, Changyu; Vatta, Matteo; Velazquez, Eric J.; Wessel, Jennifer; Kimaiyo, Sylvester; Inui, Thomas S.; Department of Medicine, IU School of MedicineBACKGROUND: There is an urgent need to understand genetic associations with atrial fibrillation in ethnically diverse populations. There are no such data from sub-Saharan Africa, despite the fact that atrial fibrillation is one of the fastest growing diseases. Moreover, patients with valvular heart disease are underrepresented in studies of the genetics of atrial fibrillation. METHODS: We designed a case-control study of patients with and without a history of atrial fibrillation in Kenya. Cases with atrial fibrillation included those with and without valvular heart disease. Patients underwent clinical phenotyping and will have laboratory analysis and genetic testing of >240 candidate genes associated with cardiovascular diseases. A 12-month follow-up assessment will determine the groups' morbidity and mortality. The primary analyses will describe genetic and phenotypic associations with atrial fibrillation. RESULTS: We recruited 298 participants: 72 (24%) with nonvalvular atrial fibrillation, 78 (26%) with valvular atrial fibrillation, and 148 (50%) controls without atrial fibrillation. The mean age of cases and controls were 53 and 48 years, respectively. Most (69%) participants were female. Controls more often had hypertension (45%) than did those with valvular atrial fibrillation (27%). Diabetes and current tobacco smoking were uncommon. A history of stroke was present in 25% of cases and in 5% of controls. CONCLUSION: This is the first study determining genetic associations in valvular and nonvalvular atrial fibrillation in sub-Saharan Africa with a control population. The results advance knowledge about atrial fibrillation and will enhance international efforts to decrease atrial fibrillation-related morbidity.Item Genomic loci influence patterns of structural covariance in the human brain(National Academy of Science, 2023) Wen, Junhao; Nasrallah, Ilya M.; Abdulkadir, Ahmed; Satterthwaite, Theodore D.; Yang, Zhijian; Erus, Guray; Robert-Fitzgerald, Timothy; Singh, Ashish; Sotiras, Aristeidis; Boquet-Pujadas, Aleix; Mamourian, Elizabeth; Doshi, Jimit; Cui, Yuhan; Srinivasan, Dhivya; Skampardoni, Ioanna; Chen, Jiong; Hwang, Gyujoon; Bergman, Mark; Bao, Jingxuan; Veturi, Yogasudha; Zhou, Zhen; Yang, Shu; Dazzan, Paola; Kahn, Rene S.; Schnack, Hugo G.; Zanetti, Marcus V.; Meisenzahl, Eva; Busatto, Geraldo F.; Crespo-Facorro, Benedicto; Pantelis, Christos; Wood, Stephen J.; Zhuo, Chuanjun; Shinohara, Russell T.; Gur, Ruben C.; Gur, Raquel E.; Koutsouleris, Nikolaos; Wolf, Daniel H.; Saykin, Andrew J.; Ritchie, Marylyn D.; Shen, Li; Thompson, Paul M.; Colliot, Olivier; Wittfeld, Katharina; Grabe, Hans J.; Tosun, Duygu; Bilgel, Murat; An, Yang; Marcus, Daniel S.; LaMontagne, Pamela; Heckbert, Susan R.; Austin, Thomas R.; Launer, Lenore J.; Espeland, Mark; Masters, Colin L.; Maruff, Paul; Fripp, Jurgen; Johnson, Sterling C.; Morris, John C.; Albert, Marilyn S.; Bryan, R. Nick; Resnick, Susan M.; Fan, Yong; Habes, Mohamad; Wolk, David; Shou, Haochang; Davatzikos, Christos; Radiology and Imaging Sciences, School of MedicineNormal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.Item Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program(Springer Nature, 2021) Taliun, Daniel; Harris, Daniel N.; Kessler, Michael D.; Carlson, Jedidiah; Szpiech, Zachary A.; Torres, Raul; Gagliano Taliun, Sarah A.; Corvelo, André; Gogarten, Stephanie M.; Kang, Hyun Min; Pitsillides, Achilleas N.; LeFaive, Jonathon; Lee, Seung-Been; Tian, Xiaowen; Browning, Brian L.; Das, Sayantan; Emde, Anne-Katrin; Clarke, Wayne E.; Loesch, Douglas P.; Shetty, Amol C.; Blackwell, Thomas W.; Smith, Albert V.; Wong, Quenna; Liu, Xiaoming; Conomos, Matthew P.; Bobo, Dean M.; Aguet, François; Albert, Christine; Alonso, Alvaro; Ardlie, Kristin G.; Arking, Dan E.; Aslibekyan, Stella; Auer, Paul L.; Barnard, John; Barr, R. Graham; Barwick, Lucas; Becker, Lewis C.; Beer, Rebecca L.; Benjamin, Emelia J.; Bielak, Lawrence F.; Blangero, John; Boehnke, Michael; Bowden, Donald W.; Brody, Jennifer A.; Burchard, Esteban G.; Cade, Brian E.; Casella, James F.; Chalazan, Brandon; Chasman, Daniel I.; Chen, Yii-Der Ida; Cho, Michael H.; Choi, Seung Hoan; Chung, Mina K.; Clish, Clary B.; Correa, Adolfo; Curran, Joanne E.; Custer, Brian; Darbar, Dawood; Daya, Michelle; de Andrade, Mariza; DeMeo, Dawn L.; Dutcher, Susan K.; Ellinor, Patrick T.; Emery, Leslie S.; Eng, Celeste; Fatkin, Diane; Fingerlin, Tasha; Forer, Lukas; Fornage, Myriam; Franceschini, Nora; Fuchsberger, Christian; Fullerton, Stephanie M.; Germer, Soren; Gladwin, Mark T.; Gottlieb, Daniel J.; Guo, Xiuqing; Hall, Michael E.; He, Jiang; Heard-Costa, Nancy L.; Heckbert, Susan R.; Irvin, Marguerite R.; Johnsen, Jill M.; Johnson, Andrew D.; Kaplan, Robert; Kardia, Sharon L. R.; Kelly, Tanika; Kelly, Shannon; Kenny, Eimear E.; Kiel, Douglas P.; Klemmer, Robert; Konkle, Barbara A.; Kooperberg, Charles; Köttgen, Anna; Lange, Leslie A.; Lasky-Su, Jessica; Levy, Daniel; Lin, Xihong; Lin, Keng-Han; Liu, Chunyu; Loos, Ruth J. F.; Garman, Lori; Gerszten, Robert; Lubitz, Steven A.; Lunetta, Kathryn L.; Mak, Angel C. Y.; Manichaikul, Ani; Manning, Alisa K.; Mathias, Rasika A.; McManus, David D.; McGarvey, Stephen T.; Meigs, James B.; Meyers, Deborah A.; Mikulla, Julie L.; Minear, Mollie A.; Mitchell, Braxton D.; Mohanty, Sanghamitra; Montasser, May E.; Montgomery, Courtney; Morrison, Alanna C.; Murabito, Joanne M.; Natale, Andrea; Natarajan, Pradeep; Nelson, Sarah C.; North, Kari E.; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Pankratz, Nathan; Peloso, Gina M.; Peyser, Patricia A.; Pleiness, Jacob; Post, Wendy S.; Psaty, Bruce M.; Rao, D. C.; Redline, Susan; Reiner, Alexander P.; Roden, Dan; Rotter, Jerome I.; Ruczinski, Ingo; Sarnowski, Chloé; Schoenherr, Sebastian; Schwartz, David A.; Seo, Jeong-Sun; Seshadri, Sudha; Sheehan, Vivien A.; Sheu, Wayne H.; Shoemaker, M. Benjamin; Smith, Nicholas L.; Smith, Jennifer A.; Sotoodehnia, Nona; Stilp, Adrienne M.; Tang, Weihong; Taylor, Kent D.; Telen, Marilyn; Thornton, Timothy A.; Tracy, Russell P.; Van Den Berg, David J.; Vasan, Ramachandran S.; Viaud-Martinez, Karine A.; Vrieze, Scott; Weeks, Daniel E.; Weir, Bruce S.; Weiss, Scott T.; Weng, Lu-Chen; Willer, Cristen J.; Zhang, Yingze; Zhao, Xutong; Arnett, Donna K.; Ashley-Koch, Allison E.; Barnes, Kathleen C.; Boerwinkle, Eric; Gabriel, Stacey; Gibbs, Richard; Rice, Kenneth M.; Rich, Stephen S.; Silverman, Edwin K.; Qasba, Pankaj; Gan, Weiniu; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; Papanicolaou, George J.; Nickerson, Deborah A.; Browning, Sharon R.; Zody, Michael C.; Zöllner, Sebastian; Wilson, James G.; Cupples, L. Adrienne; Laurie, Cathy C.; Jaquish, Cashell E.; Hernandez, Ryan D.; O'Connor, Timothy D.; Abecasis, Gonçalo R.; Epidemiology, Richard M. Fairbanks School of Public HealthThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.Item Whole Genome Sequence Association Analysis of Fasting Glucose and Fasting Insulin Levels in Diverse Cohorts from the NHLBI TOPMed Program(Springer Nature, 2022-07-28) DiCorpo, Daniel; Gaynor, Sheila M.; Russell, Emily M.; Westerman, Kenneth E.; Raffield, Laura M.; Majarian, Timothy D.; Wu, Peitao; Sarnowski, Chloé; Highland, Heather M.; Jackson, Anne; Hasbani, Natalie R.; de Vries, Paul S.; Brody, Jennifer A.; Hidalgo, Bertha; Guo, Xiuqing; Perry, James A.; O’Connell, Jeffrey R.; Lent, Samantha; Montasser, May E.; Cade, Brian E.; Jain, Deepti; Wang, Heming; D’Oliveira Albanus, Ricardo; Varshney, Arushi; Yanek, Lisa R.; Lange, Leslie; Palmer, Nicholette D.; Almeida, Marcio; Peralta, Juan M.; Aslibekyan, Stella; Baldridge, Abigail S.; Bertoni, Alain G.; Bielak, Lawrence F.; Chen, Chung-Shiuan; Chen, Yii-Der Ida; Choi, Won Jung; Goodarzi, Mark O.; Floyd, James S.; Irvin, Marguerite R.; Kalyani, Rita R.; Kelly, Tanika N.; Lee, Seonwook; Liu, Ching-Ti; Loesch, Douglas; Manson, JoAnn E.; Minster, Ryan L.; Naseri, Take; Pankow, James S.; Rasmussen-Torvik, Laura J.; Reiner, Alexander P.; Reupena, Muagututi’a Sefuiva; Selvin, Elizabeth; Smith, Jennifer A.; Weeks, Daniel E.; Xu, Huichun; Yao, Jie; Zhao, Wei; Parker, Stephen; Alonso, Alvaro; Arnett, Donna K.; Blangero, John; Boerwinkle, Eric; Correa, Adolfo; Cupples, L. Adrienne; Curran, Joanne E.; Duggirala, Ravindranath; He, Jiang; Heckbert, Susan R.; Kardia, Sharon L.R.; Kim, Ryan W.; Kooperberg, Charles; Liu, Simin; Mathias, Rasika A.; McGarvey, Stephen T.; Mitchell, Braxton D.; Morrison, Alanna C.; Peyser, Patricia A.; Psaty, Bruce M.; Redline, Susan; Shuldiner, Alan R.; Taylor, Kent D.; Vasan, Ramachandran S.; Viaud-Martinez, Karine A.; Florez, Jose C.; Wilson, James G.; Sladek, Robert; Rich, Stephen S.; Rotter, Jerome I.; Lin, Xihong; Dupuis, Josée; Meigs, James B.; Wessel, Jennifer; Manning, Alisa K.; Epidemiology, School of Public HealthThe genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.Item Whole Genome Sequencing Analysis of Body Mass Index Identifies Novel African Ancestry-Specific Risk Allele(medRxiv, 2023-08-22) Zhang, Xinruo; Brody, Jennifer A.; Graff, Mariaelisa; Highland, Heather M.; Chami, Nathalie; Xu, Hanfei; Wang, Zhe; Ferrier, Kendra; Chittoor, Geetha; Josyula, Navya S.; Li, Xihao; Li, Zilin; Allison, Matthew A.; Becker, Diane M.; Bielak, Lawrence F.; Bis, Joshua C.; Boorgula, Meher Preethi; Bowden, Donald W.; Broome, Jai G.; Buth, Erin J.; Carlson, Christopher S.; Chang, Kyong-Mi; Chavan, Sameer; Chiu, Yen-Feng; Chuang, Lee-Ming; Conomos, Matthew P.; DeMeo, Dawn L.; Du, Margaret; Duggirala, Ravindranath; Eng, Celeste; Fohner, Alison E.; Freedman, Barry I.; Garrett, Melanie E.; Guo, Xiuqing; Haiman, Chris; Heavner, Benjamin D.; Hidalgo, Bertha; Hixson, James E.; Ho, Yuk-Lam; Hobbs, Brian D.; Hu, Donglei; Hui, Qin; Hwu, Chii-Min; Jackson, Rebecca D.; Jain, Deepti; Kalyani, Rita R.; Kardia, Sharon L. R.; Kelly, Tanika N.; Lange, Ethan M.; LeNoir, Michael; Li, Changwei; Marchand, Loic Le; McDonald, Merry-Lynn N.; McHugh, Caitlin P.; Morrison, Alanna C.; Naseri, Take; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; O'Connell, Jeffrey; O'Donnell, Christopher J.; Palmer, Nicholette D.; Pankow, James S.; Perry, James A.; Peters, Ulrike; Preuss, Michael H.; Rao, D. C.; Regan, Elizabeth A.; Reupena, Sefuiva M.; Roden, Dan M.; Rodriguez-Santana, Jose; Sitlani, Colleen M.; Smith, Jennifer A.; Tiwari, Hemant K.; Vasan, Ramachandran S.; Wang, Zeyuan; Weeks, Daniel E.; Wessel, Jennifer; Wiggins, Kerri L.; Wilkens, Lynne R.; Wilson, Peter W. F.; Yanek, Lisa R.; Yoneda, Zachary T.; Zhao, Wei; Zöllner, Sebastian; Arnett, Donna K.; Ashley-Koch, Allison E.; Barnes, Kathleen C.; Blangero, John; Boerwinkle, Eric; Burchard, Esteban G.; Carson, April P.; Chasman, Daniel I.; Chen, Yii-Der Ida; Curran, Joanne E.; Fornage, Myriam; Gordeuk, Victor R.; He, Jiang; Heckbert, Susan R.; Hou, Lifang; Irvin, Marguerite R.; Kooperberg, Charles; Minster, Ryan L.; Mitchell, Braxton D.; Nouraie, Mehdi; Psaty, Bruce M.; Raffield, Laura M.; Reiner, Alexander P.; Rich, Stephen S.; Rotter, Jerome I.; Shoemaker, M. Benjamin; Smith, Nicholas L.; Taylor, Kent D.; Telen, Marilyn J.; Weiss, Scott T.; Zhang, Yingze; Heard-Costa, Nancy; Sun, Yan V.; Lin, Xihong; Cupples, L. Adrienne; Lange, Leslie A.; Liu, Ching-Ti; Loos, Ruth J. F.; North, Kari E.; Justice, Anne E.; Biostatistics and Health Data Science, School of MedicineObesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10−9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.